DocumentCode :
57090
Title :
Nonrigid Registration of Volumetric Images Using Ranked Order Statistics
Author :
Tennakoon, R.B. ; Bab-Hadiashar, Alireza ; Cao, Zhichao ; de Bruijne, Marleen
Author_Institution :
Fac. of Eng. & Ind. Sci., Swinburne Univ. of Technol., Hawthorn, VIC, Australia
Volume :
33
Issue :
2
fYear :
2014
fDate :
Feb. 2014
Firstpage :
422
Lastpage :
432
Abstract :
Nonrigid image registration techniques using intensity based similarity measures are widely used in medical imaging applications. Due to high computational complexities of these techniques, particularly for volumetric images, finding appropriate registration methods to both reduce the computation burden and increase the registration accuracy has become an intensive area of research. In this paper, we propose a fast and accurate nonrigid registration method for intra-modality volumetric images. Our approach exploits the information provided by an order statistics based segmentation method, to find the important regions for registration and use an appropriate sampling scheme to target those areas and reduce the registration computation time. A unique advantage of the proposed method is its ability to identify the point of diminishing returns and stop the registration process. Our experiments on registration of end-inhale to end-exhale lung CT scan pairs, with expert annotated landmarks, show that the new method is both faster and more accurate than the state of the art sampling based techniques, particularly for registration of images with large deformations.
Keywords :
computerised tomography; image registration; image sampling; image segmentation; lung; medical image processing; pneumodynamics; statistical analysis; deformations; end-inhale-to-end-exhale lung computerised tomography scan pairs; expert annotated landmarks; high computational complexities; intensity based similarity measures; intramodality volumetric images; medical imaging applications; nonrigid volumetric image registration; order statistics based segmentation method; ranked order statistics; registration accuracy; registration computation time; sampling scheme; Accuracy; Computed tomography; Cost function; Lungs; Mathematical model; Noise; Biomedical imaging; nonrigid registration; ranked order statistics; robust statistics; sampling;
fLanguage :
English
Journal_Title :
Medical Imaging, IEEE Transactions on
Publisher :
ieee
ISSN :
0278-0062
Type :
jour
DOI :
10.1109/TMI.2013.2286192
Filename :
6636067
Link To Document :
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